ABSTRACT Suicide is the 10th leading cause of death, with over 47,000 preventable deaths per year in the U.S. alone. The rate of suicide death across the U.S. has risen by 33% over the past two decades. In spite of this dramatic public health crisis, suicide research lags far behind other major health conditions due to the perception that risk factors are too complex and uncontrollable for study. Importantly, while environment has undeniable impact, evidence suggests that genetic factors play a major role in suicide death. While the study of genetic risks is therefore promising, most studies of suicide genetics have focused on the much more common traits of suicidal thoughts and behaviors. This strategy has allowed other research groups to acquire sufficiently statistically-powered samples. However, suicidal behaviors can be difficult to quantify, and represent individuals with a wide range of risk for later suicide death. Using the unique resources available to the Utah Suicide Genetic Risk Study (USGRS), we are able to study the genetic risks of the unambiguous, high-impact health outcome of suicide death directly. The USGRS currently has DNA from >6,000 population-ascertained suicide deaths; this resource grows by ~650 cases per year through an unprecedented two-decade collaboration with the Utah Department of Health?s centralized Office of the Medical Examiner (OME). We have completed whole genome sequence (WGS) data on a subset of 281 of the Utah suicide deaths selected for high genetic risk. We have Illumina PsychArray data on these cases and additional Utah suicides (total N=4,382). All cases are linked to the Utah Population Database (UPDB), a statewide resource that includes demographic data and comprehensive medical records. The UPDB phenotypic data also includes unique information on familial risk far exceeding that of other data resources through genealogical records that go back to the 1700s. To truly understand risk of suicide death and to implement highly effective interventions that provide appropriate, targeted services to those most likely to die, we must understand the risks specifically associated with suicide deaths. This proposal focuses on the identification, validation, characterization, and replication of variants with high functional impact that implicate genes and gene pathways important for risk of suicide death. From our WGS data, we have already detected high-impact structural variants (SVs) and single nucleotide variants (SNVs) showing genome-wide significant gene pathway enrichment and protein-protein interactions. These pathways are also supported by genes implicated in our genome-wide association analyses of 3,413 Utah suicide deaths, suggesting overlap at the functional level of rare and common risk variation. Extensive familial risk data and large sample size will allow us to select an additional subset of 760 suicides with enhanced genetic risk to replicate and extend our current findings, setting the stage for identification of high-risk individuals, and for development of targeted interventions.